{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./log.txt',header=None,sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>api</th>\n",
       "      <th>请求数</th>\n",
       "      <th>请求总时长</th>\n",
       "      <th>res_time_min</th>\n",
       "      <th>res_time_max</th>\n",
       "      <th>res_time_avg</th>\n",
       "      <th>请求间隔</th>\n",
       "      <th>create_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019162542</td>\n",
       "      <td>/front-api/bill/create</td>\n",
       "      <td>8</td>\n",
       "      <td>1057.31</td>\n",
       "      <td>88.75</td>\n",
       "      <td>177.72</td>\n",
       "      <td>132.0</td>\n",
       "      <td>60</td>\n",
       "      <td>2018-11-01 00:00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>162644</td>\n",
       "      <td>/front-api/bill/create</td>\n",
       "      <td>5</td>\n",
       "      <td>749.12</td>\n",
       "      <td>103.79</td>\n",
       "      <td>240.38</td>\n",
       "      <td>149.0</td>\n",
       "      <td>60</td>\n",
       "      <td>2018-11-01 00:01:07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id                     api  请求数    请求总时长  res_time_min  \\\n",
       "0  2019162542  /front-api/bill/create    8  1057.31         88.75   \n",
       "1      162644  /front-api/bill/create    5   749.12        103.79   \n",
       "\n",
       "   res_time_max  res_time_avg  请求间隔            create_at  \n",
       "0        177.72         132.0    60  2018-11-01 00:00:07  \n",
       "1        240.38         149.0    60  2018-11-01 00:01:07  "
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = ['id','api','请求数','请求总时长','res_time_min','res_time_max','res_time_avg','请求间隔','create_at']\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.drop('api',axis=1)#api的值都是一样的所以删掉。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.index=pd.to_datetime(df['create_at'])#将时间作为索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.drop(['请求间隔','id','create_at'],axis=1)#请求间隔都是60秒所以删掉"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['2019-5-1']['请求数'].plot()\n",
    "plt.show()\n",
    "#由图可知2019-5-1这一天的访问高峰为下午两三点和晚上八九点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['2019-5-1'][['请求数']].boxplot(showmeans=True,meanline=True)\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=df['2019-5-1'].resample('20T').mean()\n",
    "data[['请求总时长','res_time_min','res_time_max','res_time_avg']].plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>请求数</th>\n",
       "      <th>请求总时长</th>\n",
       "      <th>res_time_min</th>\n",
       "      <th>res_time_max</th>\n",
       "      <th>res_time_avg</th>\n",
       "      <th>weekday</th>\n",
       "      <th>weekend</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>create_at</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-11-01 00:00:07</th>\n",
       "      <td>8</td>\n",
       "      <td>1057.31</td>\n",
       "      <td>88.75</td>\n",
       "      <td>177.72</td>\n",
       "      <td>132.0</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-11-01 00:01:07</th>\n",
       "      <td>5</td>\n",
       "      <td>749.12</td>\n",
       "      <td>103.79</td>\n",
       "      <td>240.38</td>\n",
       "      <td>149.0</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     请求数    请求总时长  res_time_min  res_time_max  res_time_avg  \\\n",
       "create_at                                                                     \n",
       "2018-11-01 00:00:07    8  1057.31         88.75        177.72         132.0   \n",
       "2018-11-01 00:01:07    5   749.12        103.79        240.38         149.0   \n",
       "\n",
       "                     weekday  weekend  \n",
       "create_at                              \n",
       "2018-11-01 00:00:07        3    False  \n",
       "2018-11-01 00:01:07        3    False  "
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['weekday']=df.index.weekday\n",
    "df['weekend']=df['weekday'].isin({5,6})\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ndf4KGqKPsFnhnSfA2gIL/wEerWOYlYIJS2DEfNj4a6Pb5OB7xrJb4xdfGI3hVg69D811F7pJqhqa+eRAIUtSYztf8MCObhgXTZi/F6t25zCno8qDMSmQ/iqUnYQBIxweT2dMSdxeXl4MGdL5Yp9CiDa2/RnObIE7/goRwy7f7hcKN/+PscjAhz+Edx6Dvf+Em/9gtMzdyd43IWI4xE0FYF1WPo0tNu5Odc6wWx9PDxYlx7J8ezalNY0MCPRpv8P5C5R5GaYm7n5bZEoIt5C/11htfOwdF1qhnRo8GR77Am75A+Rnwd9nwhf/BU1XmMrtSs6dNOpeT7rvwreFNem5jIoOYnxMiNPCWDo1jmarZm1G7uUbB4w0aqeY3M8tiVsIV9VUC2sfM0qK3vp/Xev6sHjAlMeMBW6TFsHXf4C/TYOjnzo+3t7KWgUomGCM3T5eVE3m2QqWpMZ2uOivowyPCmJKYhhv7T57+XU4i4fxD1IStxCiQ+t/ZrRCF75kTLnujsAo43nf/Ag8/WDlPcbyW67KZoOslTBsLoTEAEZBKU+L4q7JMU4PZ+mUeE6V1rLzdNnlG2OSjYqmLY1Oj+s8SdxCuKLDH0LG6zDr+70rapR4DTy5xWh97/qHUZbUFWVvhsqzF7qDmq023tmTy/Vjooi4tJ/ZCYxCVp6s3JVz+caYFLA2QdEBp8d1niRuIVxNVQF88D0YNBHm/rz3x/P0hmlPgrURjn7c++M5QuYK8AmB0bcAsOloCaU1TXYvKNVVft4e3DU5hk8OFFJR19R+44ULlObNoJTELYQrsdngvW9Dc70xRtvT2z7HjZ0CIXFwYK19jmdPDVVw6ANIWmhMcsEYux0Z5EPaqJ4tBmwPS6fE09Ri4509ee03BMdAYLSp/dySuIVwJTv/Dqc2wo2/se9QPqWMSS0nv4S6DvptzXToPWipv9BNUlLdyMYjxSyc3LvFgHtr7OBgJsaFsmp3TvuLlC6wlJkkbiFcReF++Pw5GHUzpDxs/+MnLQJbi7FAgSvJXGmM3Y41Svu/tzePFptmSar5k9bunRLHsaIa9uRcMiM1JhlKj0FDjyaP95okbiFcQXO9MfTPLwxu/4tjZj0Omgjhw4yaJ66i7LQxdnvivaCUsRhwxlkmx4cyPCrI7Oi4beJgArw9WHXpRcoLlQLNqREjiVsIV/DZf0LJEbjzbxAwwDHnUMpodWd/DdVXWNXcmc6P3W6tu70vt5JjRTWmXZS8VICPJ7dPGsyH+wqobmi+uGHwZOM2N92UuCRxC2G2Yxtg1zKY/h0YPs+x50paBNpm1AQx2/mx20PmQIjRLbI6/Sy+XhZunWjuQgVt3T4xhvpmK7vajun2CzO6d0waWSKJWwgz1RTD+9+BqHFw/S+uuntpTSPffG0Xz39ymIbmHlRUjhptnMsVRpfkbIeKM8YUd6Ch2coHWfnclDSIYDsuBtxbk+ND8fJQpJ8pb78hJgXy0sGEKqeSuIUwi9bw/lPGcLhFL4PXlUv/5lfUc/dL29l24hwvfXWKG/9vMztPnev+eZPugrM7oKKTBQOcJWuFUfdjzG1A62LADS0ucVGyLV8vD8YNDiEju4PEXVMEVflOj0kStxBmObURjm+Aec9B9Ngr7nq6tJYlL26npKqRNx6bxorHpmHVmnuW7eDZ9w5Q09jS9fOOW2jcHny3x6H3WlMdHHzfKJ7lHQAYBaViw/yYPiTCvLg6MSUxjMzcChpb2nzLaVsp0MkkcQthlqxV4BsCqY9ccbcjhVUseXE79c1WVj4+nalDwpk5fADrfzCHh2cl8sbOM9zwx81svtIK5W1FDDMurpnZXXLkQ2iqNkaTALnldWw9WcqSlDiHLAbcWykJ4TS12DiQ16ZkQHQSWLwkcQvRbzRWw+F1Ruv3Cl0ke3PKueelHXhYYPUT00lqU97U39uTX9w2jrefnIGvl4UHX93Fj9ZkUVnX3OnxLkhaBAWZRhErM2SugJB4SJgFwNoMY3biohTnF5TqipSEMADSs9tcoPTyhYFJkriF6DcOfdC60st9ne6y7WQp97+8kxA/L95+cman45pTEsL56PuzeWruMN7dm8e8P37F+oOFVz7/uLuMWzPGdFfmwalNxhBAiwWbzRi7PWvYAGLD/J0fTxdEBvkwZEBAxxco8zOdvmCzJG4hzJC1EsKHGjVEOvD5oSK++dpuYsP8WPPkDOLCr5zQfL08+PENo3n/qVkMCPThiX9l8NSKPZTWdFJ6NCQW4mfAQRMS9763AH1h7Pau7DJyyx2/GHBvpSSEkXGmvP3095gUo8un9LhTY5HELYSzVeQYk2BaZwte6v3MPJ54I4PRA4N46/EZRAd3faHppJgQPvjuLH60YCSfHSxi/v9+xfuZeR0vzJ20CIoPQdGh3rya7tHa+KcVN/3CMmxrM3IJ9HHOYsC9kZoQRlltE6dKay8+aNIFSkncQjjbvtXG7YS7L9v05s4z/OCtTFITwnjzsWmEBXS/OqCXh4XvXjeCj75/DQkRAfzbqkweW55OYWVD+x3H3gHK4txWd94eo8bHJOOiZH2TlY/3F3Dz+IH4eTt+MeDeSE00FrNoNywwYgR4B0niFqJP09oYTZIwC8IS22168auTPPPuAeaOimL5I1MJ6uUklBHRQaz99kx+fssYtp4s5eHXd7dveQdGQeJsY3SJsyaRZK0AT98LfezrDxZS22RlYbJrd5MADIsMIMzfi91tL1BaLBDj/KXMJHEL4Ux5GXDu+IVhcABaa/5n/RF++8kRbp0wiBcfSMHXyz6tTw+L4rHZQ/nl7eM4XFDFjlOXlHRNWgRlp4wRJo7W0gj73zYWS/A1Rses3WOM3Z6a2M2l2UyglCIlIZyMji5QFh2A5oaOn+gAkriFcKaslUaLc+wdANhsmuc+OMhfN55k6ZQ4/rR0Mt6e9v+zvGNSDKH+Xizflt1+w5jbwOLpnDHdxz6FhgqYaIykKaxsYOuJUhYmx7rk2O2OpCaGcaq0lnNtL/rGpBjlcgv3Oy0OSdxCOEtLo5EgR98KvsHYbJofv72P5dvP8K3ZQ3h+4Xg8HJTAfL08uGdKHBsOFZJXUX9xg384DLseDrxrFH1ypMyVEDjQWBAYeHdvHjYNC01YDLinUs+P527b6jbhAqUkbiGc5fgGqC+/0E3y8YEC1u7J5fvXj+BnN49BOaIGdxvfmJ4AwBs7zrTfkLQIqnIhd5fjTl5TAic+g4n3gMUDrTXv7MklNSGMxAEBjjuvnY2PDcHb09K+uyR4MAQNksQtRJ+UtcpYq3BoGlpr/vH1aRIj/Pm360c4PGkDxIb5M29MNKt25bSvLDjqJqP7xpGTcfavMboTWrtJ9udVcry4xi0uSrbl4+nBhJiQ9jMowelLmXU7cSulwpRSHyul0pVSLzkiKCH6nNpzcGy9MQTQw5P0M+Vkna3g0dlDHdY90pFvzkykvK6ZD7LaVLTzDYYRC4yiU46aAZi1wqiPEjUagHf25OHtaeGWCa5Td7urUhLD2J9X2f6fX0wylJ102nqePWlxfwN4U2udCgQppVLtHJMQfc+BtWBrvtBN8o/Npwjz92Kxk1ucM4ZFMDI6kOXbstsPDUxaCLXFkL3F/ictPGBcuGttbTe12Hg/M4/5Y6MJ8XOduttdNSUhnGarZl9um/UmnbyUWU8S9zkgSSkVCsQBJhf1FcINZK2EgeMhehynS2v57HARD0xPcPqkE6UUD85I5GB+Vft+2hE3gFeAY0aXZK00quiNXwzApqPFlNc1O/2flr2cLzjVbjz3+aXMnLQiTk8S9xYgAfg+cBi47LuBUurx1q6U9JKSLpaaFKKvKjkK+XsutLZf2XIKL4uFb8xIMCWcuybHEOTryetthwZ6+8Pom40V4Fua7Hcya4sxU3TkDcYIFoyx2wMCfZg9wkFrazpYWIA3wyID2v/j8w2BASOd1s/dk8T9C+BJrfV/AUeAhy/dQWu9TGudqrVOjYyM7G2MQri3rJWgPGD8Esprm3g7I5c7Jw8mKqjrNUjsKcDHk7tT4/j0QCFFVW0mjSQtMka9nNpkv5Od/MLogmmtglhe28SXR4q5c9JgPD3cd2zElERjIo7NdknBqbwMp8xC7ck7FwaMV0p5ANMA5y+4JoS7sFmNFufweRAYxRs7ztDQbOOx2UNNDevBGQlYtebNtkMDh11ntBzt2V2SuQL8I2D4fADW7cun2apZ5OKVAK8mJSGMyvpmTpTUXHwwJsX4J1WZ6/Dz9yRxPw8sAyqBcGClXSMSoi/J/hqq8mDiUhqarSzffoZrR0YyMrrj2trOkhARwNxRUazYlXNxOS5PH2Mm5ZGPoLn+ygfoivpyOPoxjF8CnkaxrLUZuYwZFMyYQcG9P76JzhecSm9bcCom2bh1QndJtxO31nqX1nqc1jpQaz1fa11z9WcJ0U9lrQKfEBh1Ex9k5lNa08i3TG5tn/fQzERKa5r4eH/BxQeTFhn1pY9/1vsTHHgHrE0X+vZPFFeTlVvJomT3mSnZmcQIfwYEercfzx2dBB7erpm4hRBd1FhjrHQz7k60py8vbznF6IFBzBruGovhzh4+gKEDAnh9W5vuksQ54D/APqVes1ZC1FgYNBGAtXvy8LAo7pjk/onbKDgV1n7qu6ePMXLICSNLJHEL4SiH10FzLUy8l6+OlXCsqIZvzR7qlFmSXWGxKB6ckUDW2Qoyz1YYD3p4GgWwjn5q/OPpqdLjkLv7wmIRVpvmvb15XDsyksggH/u8AJOlJoSTU1ZHcdsLvDEpxlhuBy9lJolbCEfJWmnU3I6fzstfnyY62IfbJg42O6p2FqXEEuDt0b5qYNIiaKk3qvn1VNZKY5GG1sUitp88R0FlAwv7QDfJeamJnRScaq41hoA6kCRuIRyhMhdOb4aJ93KooJotJ0r55swhDinZ2htBvl4sTonlw335lFS3liqNn2EUTerp6BKb1ejbH3Y9BBnLka3dk0uwryfzxkTbKXLzjRscgo+n5ZILlM6pFOhanyIh+op9qwENE+7h5S2n8Pf24L6p8WZH1aEHZybSbNWs3JVjPGCxwLiFxgXK+vIrP7kjpzcbI2lalyeraWzh0wOF3DpxsN0WiHAF3p4WJsWFknGmzQXK8GHGxWhJ3EK4mfPLk8XPoNBjEB9k5nN3ahwh/q5Zl2NYZCCzRwzgzZ1naLa21uROWmTUVjnyUfcPmLWydSTNLQB8sr+A+mZrnxhNcqnUxDAO5FdR19RiPOCkpcw8HXp0Ifqj/D1QehRu+xOvb8vGpjWPXjPE7Kiu6JszE3l0eTqfHig0+uFjkiE0ATKWg18YaJvRBaKtxj8mm9V4TFsvuW8zLspOuBu8jJmh7+zJIzHCn+T4MJNfpf2lJoRjtZ0k82wFM4e1TuGPSYEt/2eMhffyc8h5JXELYW9Zq8DDh9rht7FiXTo3Jg0kLtzf7KiuKG1UFPHh/izflm0kbqVgwj2w+Xew6r7uHUx5QPJDAOSW17H91Dn+ff5IlxlNY0/J8WEoZUzEaZe4tRUK9kH8NIecVxK3EPbU0nRhQdzVB6qoamgxfXp7V3i0Dg381UeHOZBXSVJMCFz7H8bCvgAWDyMhK0vrfUub+x7t73v6gE8gAO/tzQOMwlZ9UYi/FyOjgjpfykwStxBu4MRnUF+GdcJSXn3/NCkJYW7TRbAkNY4/bDjG8m3Z/M+SieDhBYMn9fh4WmvW7slj2pBwl//G0RspiWGsy8zHatPGohhBAyE4xqH93HJxUgh7ylwBAZFsaBjL2bJ6vjXbtfu22wrx8+Ku5Bjez8qnrLb3pV335FRwurTW7QtKXc2UxDCqG1s4Wlh98cGYZEncQriFujJjebLxd7Nsaw4JEf7MHzvQ7Ki65aEZiTS12Fi1O6fXx3pnTy6+XhZuHu9+y5N1R2qCUXCq3bDAmBQoP+2wpcwkcQthL63Lkx2Kupm9ORU8MmuIU9eTtIdRA4OYMTSCN7afoeX80MAeaGi2si4rnxvHDSTQp2/3yMaG+REV5MPuDifiOKZuiSRuIewlaxVEJ/Hng36E+HmxJNU9uwgemplIfmUDnx8u6vExvjxSTFVDS5/vJgGj4NT5hRUuGDQJvAOhOr/zJ/aCJG4h7IhBjuMAABf5SURBVKH0OOSlUzZ8IesPFfLA9Hj8vd2zpTlvTBQxoX7tlzbrprUZuQwM9r04RK6PS0kII6+invyK1jrmvsHwdA4kP+iQ80niFsIeDr0PwCuVyXhZLDw0I9HceHrB08PCA9MT2HGqjCOFVd1+fmlNI5uOlXDn5Bi36yrqqQ4LTlkcN71fErcQ9pC9BWvkWF7NauT2SYOJCjZnPUl7WTolDh9PC69uOU1TS/f6ut9vHRrXF6e4d2bsoGD8vT3IyHbMxchLued3OSFcSUsTnN3JwajbqG+28pgbDQHsTFiAN3dOiuGt9LOsTs8l1N+LyEAfIoNaf1rvRwX7EBnoe+HxUD8v1mbkMiE2hBEmL8/mTJ4eRsGpdi1uR57PKWcRoi/L3wvNdbxRGM/sEQMYPdC911M877nbx5GcEEpRVSMl1a0/NY3szamguLqBhubLW+KeFkWLTfPcbWNNiNhcqQlhvLDxBDWNLQ4fSSOJW4jeOrMFgM9qh/EnN5je3lV+3h7cM6XjUrRaa2qbrBcTenUjJdUNlNQ00tBsY3FqnJOjNV9qYjg2DXtzypk9ItKh55LELURvZW8hz3sI3t6RzB7RP0ZRKKUI9PEk0MeTIQMCzA7HJUyOD8WiYHe24xO3XJwUojeszeicHXzVNIq5o6L6ZAU80TVBvl6MHhjcfgalg0jiFqI38veimuvY3DSatFFRZkcjTJaaGMbenIpezTrtCkncQvRG9tcA7FVjmDU8wuRghNlSEsKoa7JyuKD66jv3giRuIXojeyvZlniGJSYS5OuaS5MJ55mSaBScSndwd4kkbiF6ytqMLWf7hf5tIQaH+jE4xLf9yu8OIIlbiJ7Kz8TSXMcO21jmjnbsKALhPlISw0k/U4bW2mHnkMQtRE+19m/nhkxiWGSgycEIVzElMYyiqkZyy+sddg5J3EL0kO301xzXsUwe3TcXwhU9k5JwvuCU4/q5e5y4lVJ/U0rdZs9ghHAb1mZsOTvZbh0j/duindEDgwn08XRoP3ePErdSajYwUGu9zs7xCOEeCrLwbKklQ41j+lAZBigu8rAoJseHtl9Ywc66nbiVUl7AP4BspdQd9g9JCDfQ2r9tS5iJn7fj6i4L95SaEM7Romoq65sdcvyetLgfBA4BvwOmKqW+d+kOSqnHlVLpSqn0kpKS3sYohMupO/YVx2wxpI4dZXYowgWlJoahNezJcUyruyeJezKwTGtdCLwBzL10B631Mq11qtY6NTJShkmJPsbaglfeTnbapH9bdGxSXChRQT5U1DU55Pg9qQ54AjhfuzIVOGO/cIRwAwVZeFnrOB04mW9E+JsdjXBBAT6e7PzZ9Q4bbdSTxP0K8KpSaingBSy2b0hCuLamk1/hDQSNSjM7FOHCHDlEtNuJW2tdDSxxQCxCuIWqwxspt8Uwdfxos0MR/ZRMwBGiO6wtBBXvJkONvbCytxDOJolbiG7QBVn42Oqpip6Gj6cMAxTmkMQtRDeUHvgCgMjx15sciejPJHEL0Q11x77ihG0w0yeMMTsU0Y9J4haiq6wtRJbv4ajvRAaF+JkdjejHJHEL0UU1ORn46zqs8TPNDkX0c5K4heiis3s+AyA+eYHJkYj+ThK3EF2kT2/hNINJGjXS7FBEPyeJW4gusLU0E1+TRV5ICp4e8mcjzCWfQCG64NSB7QRSh9ewOWaHIoQkbiG6ojDrcwCGT73R5EiEkMQtRJf45G0nzyOGiIHxZocihCRuIa6mrLqeUY37KYucanYoQgCSuIW4qqz0rwlW9QSPvmzNECFMIYlbiKuoPPQlAHGT55sciRAGSdxCXIHVpgkt2UWxdyyWkMFmhyMEIIlbiCvKPHOOZH2Y+sEzzA5FiAskcQtxBYf2biVY1RGZJGVcheuQxC3EFTQc/woA/5HXmhyJEBdJ4haiE0VVDSTW7KXCLw6CpX9buA5J3EJ0YvORQqZajqATrjE7FCHakcQtRCeO7d9BiKojdIyM3xauRRK3EB1ottrwzNkKgEqUFrdwLZK4hehAenY5ybaD1AXEQ0iM2eEI0Y4kbiE6sOlIAVMtR/AaLmVchevxNDsAIVzRmUO7CVG1MFQSt3A90uIW4hJny+oYXJFh/JI4y9xghOiAJG4hLrHpWAnTLYdoDk6EkFizwxHiMpK4hbjEl4cKmO5xFM+hMppEuKYeJ26lVLRSaq89gxHCbJV1zZSe3EswNaghs80OR4gO9abF/XvAz16BCOEKPjtcRCoHjV8SpH9buKYeJW6l1HVALVBo33CEMNfH+wtY4HMQHZYIoXFmhyNEh7qduJVS3sCzwNNX2OdxpVS6Uiq9pKSkN/EJ4TSV9c0cOH6SqToLNfYOs8MRolM9aXE/DfxNa13R2Q5a62Va61StdWpkZGTPoxPCiT4/VMR8duKhrZC02OxwhOhUTxL3POAppdQmYJJS6mX7hiSEOT45UMAS7x3oAaNg4HizwxGiU92eOam1vjCVTCm1SWv9mH1DEsL5qhqaOX7sCJO8DsH4n4NSZockRKd6NY5ba51mpziEMNUXh4u4EaMaIOMXmRuMEFchE3CEAD7eX8gi7+3omFQIH2p2OEJckSRu0e9VNzSTd2wPI3U2avwSs8MR4qokcYt+78sjxdzEVrSywLi7zA5HiKty7cSttdkRiH7g43353OW5HYZcC0HRZocjxFW5buLe8y/461RoaTI7EtGH1Ta2UHZsO7EUSTeJcBuum7iDBkLpMTiyzuxIRB/2xZFibmYLNos3jLnV7HCE6BLXTdzDrofQBNj9itmRiD5s/b5cbvfciRp1I/iGmB2OEF3iuonbYoEpj8KZrVB00OxoRB9U19RC/bGNRFCBGi9T3IX7cNnEve1kKc+dnYz28JFWt3CIL48Uc5PeQotXIIxYYHY4QnSZyybuvPJ6Xs+spij+Ftj3FjRUmR2S6GM+y8rmJs/dWMbeDl5SWl64D5dN3LdPGkxUkA9/r02DphojeQthJ3VNLehjnxFIPZYJMppEuBeXTdw+nh48PGsIy3MiqB8w3ugukXHdwk42HS3hRrbQ5DsAEudc/QlCuBCXTdwA902LJ8Dbk/c8b4KSw3Bmm9khiT7ii8zjXO+xF88Ji8Cj20UyhTCVSyfuED8vlk6N51c5Y7H5hMLuf5gdkugD6pus+Bz/GB+asUy42+xwhOg2l07cAI9cM4QGfNgVehMcXgfVssyl6J2vjhVzo95CfWA8xKSYHY4Q3ebyiTsm1I/bJgzilwXTwNYCe/5pdkjCzW3ee5BZHgfxmXS3LJgg3JLLJ26Ab80ZyuGmKHLCpkP6a2BtMTsk4aYamq0EHl+HBzYsE6WbRLgnt0jc4waHcM3wAfy56lqozodjn5gdknBTXx0r4Sa2UBM2BiJHmR2OED3iFokb4PE5Q3mndjy1foNgl1ykFD2zMyOdyZYT+CXfY3YoQvSY2yTu2SMGMHJgCG/ZrofTX0HJMbNDEm6modlK6Emj2qSH1CYRbsxtErdSisfnDOVvlbOwWbwg/VWzQxJu5utjJdykv6YicgqExpkdjhA95jaJG+C2iYPxDI5mu88syFwBTbVmhyTcSGb6FkZY8giastTsUIToFbdK3F4eFh65JpE/VsyBxkrY/7bZIQk30dhiJeLU+1jxwEPWlRRuzq0SN8C9U+M56j2OPO+hxkxKqV8iumDLsWJuYCvlg2dDQITZ4QjRK26XuIN8vbhvWgJ/q50Lhfshd7fZIQk3cGjnBmLUOUKn3md2KEL0mtslboBvzkpknb6GRos/7H7Z7HCEi2tssRJ1Zh2NyhfPMbeYHY4QveaWiXtQiB/zJg1lTcts9MF3obbU7JCEC9t+rJD5ejvlcfPAJ9DscIToNbdM3GBMyHm9+XqUtQn2/svscIQLO7FjHeGqhogZ95sdihB24baJe/TAYAaPmEy6Godt96tgs5odknBBTS02Buaso84ShNeIeWaHI4RddDtxK6VClFKfKKU2KKXeVUp5OyKwrnhizlBeaZyHpTIHTnxuVhjChW0/msNcvZuyxJvB07SPqhB21ZMW9/3A/2qtFwCFwI32DanrZg6LIC96LqUqDC31S0QHcre/Q4BqJGrWA2aHIoTddDtxa63/prX+rPXXSKDYviF1nVKKR68dyRvNc40Wd9kps0IRLigju4zYnPep8IzEe8g1ZocjhN30uI9bKTUDCNNa7+hg2+NKqXSlVHpJSUmvAryam8cPYmPAzdhQRq1uIYATxdXsWP4011oy8Zr2CFjc9nKOEJfp0adZKRUO/AV4pKPtWutlWutUrXVqZGRkb+K7Ki8PC7fPTmW9NZWWjH9Cc71DzydcX0FlPetf+ilP6beoGX03Adc/bXZIQthVTy5OegNrgJ9qrc/YP6Tuu2dKHGs9bsSzsQIOvmd2OMJElXXNvPv3Z3nK+i8qht1O4N0vSmtb9Dk9+UQ/CiQDzyilNimlTK9IH+jjychpN3PCNpjG7S+ZHY4wSUOzlVUv/pLvNPyDc3ELCL3vVbB4mB2WEHbXk4uTf9dah2mt01p/3nJEYN318KwhrNDz8SnaC5krzQ5HOFmL1cbKZc/zRNVfKBp4LREPvQkeXmaHJYRD9JnvkFHBvjQk3cduPRreexI2PCuTcvoJrTVvv/5HHir+PXnh04l+dLWM2RZ9Wp9J3ACPXpfEt/SzvMUC2PZnWHE31JebHZZwsA9XvcTinF+RGzyZmCffBS9fs0MSwqH6VOIeFhnIe9+fy8rIH/B082O0nNiEbdlcKD5idmjCQTZ+sJwbj/yM3ICxxH33A/D2NzskIRyuTyVugMQBAax5cgbRaU9wb9MzlJeXY/3H9XDkY7NDE3a2+/M1zMz4d3J9hhH71IconyCzQxLCKfpc4gZjbPcP54/k6Sce5nHf33OwMQpW3Yt14/8HNpvZ4Qk7OLTtI8Z//W3yveIZ+NQneAaEmR2SEE7TJxP3eSkJYSz/4V2sGPcS71ivweOr31D75gPQWGN2aKIXzuz9gsQND1PoMZCwJz7CL2SA2SEJ4VR9OnGDMcb7t/dMxXfJP/g9D+J74mMqXkhDl502O7SuqSmGo5/Kivatig5vZcD791NCBD6PfkRo5GCzQxLC6TzNDsBZbp4wmMkJv+N3/xrNt0t+Te0Ls7Etfp3gsS5Yo7mxBo58BPtXw8mNoK3gFwZTn4Cpj/fbxW4rT6Xj/9YSygnC+o33GBSTYHZIQphCaQevkp6amqrT09Mdeo7usNk0az7bzORt32Goyic7+acMv+3HoJS5gVlb4NRG2LcajnwIzXUQEg8TlkDsFMhYDsc+AS9/mPwNmPldCI03N2ZHsVmh4gyUnsBWeozK3MM0FR4lqOwAFdqfksXvMXH8BLOjFMKhlFIZWuvUDrf1t8R93pHsfM698TCzWnaQGX4zEXf8mshB8fh6O+5LSGOLlbpGK16eFrw8FN4Whcrfa7SsD6yF2hLwDYVxd8GEeyBuWvs6G8WHYeufjf21hvGLYda/QfQ4h8XsUHVlcO4ElB6Hc8eh9DjWkuOo8lNYbM0XdivXgZzSgzjrEU/kTT9l1tQpJgYthHNI4u5EQ1MzO177CWkFrwBQpf3JVjEUecVR7p9IfchQdPgIfKKHExUaRHSwL4NCfAkP8Ea1ttC11lQ1tFBS3UhxdQMl1Y2t9xsvPFZc1UhJTSMVdUYyildF3GnZyp0eWxhqKaRRe7FZpbDB81oyvFJQnj54e3rg7WnB20Ph7+3JyOhAxg0OYdzgYIZ6V+Cx8++Q8To018KIBXDNDyF+hvnfHMAYuVNfBlX5UF0I1QVtfgqNx6vyoO7chadY8SDXMoijzdGc0oM5zSCsYcMJTxjL6KFDSI4PIyHC/8L7LkRfJ4n7Kk5mbab6+HY8yo4TUHWKsPpswqwXk0qLtnBGGwnlpB5MNjGU+ydQYwmkrqYGi7UBP9WEL0340YivaiLQ0swAHyvhPjbCvFoI8WwhyLOFqPqTRFXuR6M4G5LCgfAb2B+SRjV+NLXYaLZqmlpsNLbYaLLaaGqxUt3QwvHiGppajKGMvl4WRg0MJjUKbm/6iHFnV+LZUAaxU+GaH8DImxxTEU9rYyZqTVFrEi66mIwvvW3TYj6vwTuCaq8IzlkiyLOGsac2gsPN0ZzSg6j1i2ViQgST48NIjg9jQmwIAT795hKMEJeRxN0TDVVw7jjW4qPUFxyhpegoHuUn8K/OxkO3dO9YHj7GNGwvfwgaaHSFJC2GkJguH6LZauNUSS0H8ys5mF/FwfxKDuVXUdXQgi+N3OPxFU96f8wgXUy5/xBKJzyBjhrbzRet8WiqxquuCK+6Yjzritrfry/BYm287FktXoHU+URR6TmAUhVGvi2MnKYQTjQEcqohmCIdRgmhNLdeCw8P8CY2zI+JsaEkJ4SSHB9GfLi0poVoSxK3PVlbWi+cHTNGf3j7g2drUvbya/Nz/nE/h5UW1VqTW17PwfwqDhVUcSSvjEG5n7C06R3GWHJ6ffwq7U+xDqVIh1GMcVvS+vv5x4p1KPVcrA0S5u/FoBA/BoX4MijU9+L91tuBIb74ekmpVSGuRhJ3P1NW00ju/q/Q9WXdfm6LZyBNftE0+kVi8/Tr0nN8PT0YFGokZknKQtjHlRK3dCL2QeGBPoTPWGB2GEIIB+nzMyeFEKKvkcQthBBuRhK3EEK4GUncQgjhZiRxCyGEm5HELYQQbkYStxBCuBmHT8BRSpUAZ3r49AFAqR3DcVfyPlwk74VB3gdDX34fErTWkR1tcHji7g2lVHpnM4f6E3kfLpL3wiDvg6G/vg/SVSKEEG5GErcQQrgZV0/cy8wOwEXI+3CRvBcGeR8M/fJ9cOk+biGEEJdz9Ra3EEKIS0jiFkIIN+OyiVsp9YpSartS6udmx2IWpZSnUipHKbWp9We82TGZQSkVrZT6uvW+l1JqnVJqq1LqEbNjc6ZL3ocYpVRum89Gh+N9+xKlVIhS6hOl1Aal1LtKKe/+midcMnErpRYCHlrrGcBQpdQIs2MyyQRgpdY6rfVnv9kBOZtSKgxYDgS0PvQ9IENrPQtYrJQKMi04J+rgfZgG/LrNZ6PEvOic5n7gf7XWC4BCYCn9NE+4ZOIG0oDVrfc3ANeYF4qppgO3KqV2tbYs+uOKRVbgHqCq9fc0Ln42NgP9ZfLFpe/DdOAxpdQepdRvzAvLebTWf9Naf9b6ayTwAP00T7hq4g4A8lrvlwHRJsZipt3APK31VMALuNnkeJxOa12lta5s81C//Gx08D58gvFPbAowQyk1wZTATKCUmgGEAWfph58FcN3EXQOcX6k2ENeN09H2aa0LWu+nA/3mq+AVyGfDsE1rXa21tgJ76SefDaVUOPAX4BH68WfBVV9oBhe/9kwEss0LxVT/UkpNVEp5AHcCWWYH5ALks2FYr5QapJTyBxYAB8wOyNGUUt7AGuCnWusz9OPPgqv2mb4HfK2UGgzchNGf1x/9F7ACUMAHWuvPTY7HFSwHPlZKzQbGAjtNjscsvwQ2Ak3Ai1rroybH4wyPAsnAM0qpZ4DXgG/0xzzhsjMnW6+izwc2a60LzY5HuI7WP9RrgPWX9PuKfqa/5gmXTdxCCCE65qp93EIIITohiVsIIdyMJG7R7yilJimlJrnq8YS4Gkncoj+a1PrjqscT4ork4qRweUopX+B1IBaoAO4GPsaYWTpBa31D63jmfwJRwH6t9VNKqUDgbYzZlie01g8rpZ4H7mo9dJ7W+vqOnttJHF06nr1fvxCXkha3cAePA1la62uAtUASxpjd7VrrG9rsc0BrPQcY1DoFfBDGLLt5QKJSKlpr/VPgt8Bv2yTZjp7bka4eTwiHctUJOEK0NRojYYPR8gYj0b7TZp9RwEylVBoQCsQAh4HHgIeBcC5Oj75UR8/d18F+zV08nhAOJYlbuIMjGMWUvgB+BhRj1Klo6yiwS2v9mlLqViAHY6bd2xgV5L5qs289EAGglFKdPLcjXTqelv5H4WDSxy1cnlLKD2OqexRwDqMu86da67Q2+wRgTIEeiFH69D6MC4Z/A8oBD+DHWuutrYWKVmO0mH+KUfOi3XO11ufLp7aNY05Xjqe13mzv90CItiRxCyGEm5GuEiE6oJTadMlDlVrrO8yIRYhLSYtbCCHcjAwHFEIINyOJWwgh3IwkbiGEcDOSuIUQws1I4hZCCDcjiVsIIdzM/w+fsXmCSZVMGgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(['weekend',df.index.hour])['请求数'].mean().unstack(level=0).plot()\n",
    "plt.show()#由图可知周末的访问量相对平时更高"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
